Introduction: Why Code for Data Science?

Phil Chodrow

Tuesday, August 27th, 2019

Some Things That Aren’t Data Science

The Cloud\(^{\mathrm{TM}}\)

Deeeeeeeeeep Learning

credit: Janelle Shane

BIG DATA!!1!!

Data Science Is:

  • Gathering data that matters.
  • Asking questions that matter about your data.
  • Choosing appropriate methods to answer those questions.
  • Implementing solutions that meet stakeholder needs.

You Can Do Data Science With:

  • A pencil and paper.
  • A calculator.
  • Excel.
  • Coding: R, Julia, Python….

Why Not Excel?

Why Code?

Version Control with git

  • Break your workflow into manageable stages; easily collaborate; access cool code.
  • Promote your brand: share your work, build a portfolio, host your website.
  • Used at: Google, Facebook, Netflix, Amazon, Apple, Twitter, Microsoft… (source)

Data Analysis with R

  • R is the best language in the world for learning data science.
  • R is one of the best languages in the world for doing data science.
  • R tends to be preferred in academia and among “statisticians,” while python is more popular among “computer scientists” and “data scientists”
  • Most practicing data scientists know and use both.

Optimization with Julia and JuMP

  • Julia is high-performance, open-source dynamic language for technical computing – easy writing, fast compute times.
  • Developed at MIT.
  • JuMP is a package for optimization in Julia – developed by ORC students!
  • Not everyone uses Julia…yet.

…yes, there will be an opportunity to learn Python later in the semester.

What can you pick up in two days?

  • You are not going to become an expert in two days.
  • But…
  • You will know the basic concepts and vocabulary of data science – enough to employ the most important skill of all.

The most important skill of all…

The most important skill of all…

Gameplan

  1. Today: Version Control, Basic Data Analysis and Visualization in R, RMarkdown.
  2. Tomorrow: Optimization in Julia and JuMP, selected presentations.
  3. Both days: mini-project, partner work, lots of exercises.

Exercise 0

  1. Look left.
  2. Look right.
  3. Pick a partner (groups of 3 are fine).
  4. Give them a professional, yet friendly smile.
  5. You are going to need them soon.